Amid what many believe is the
worst financial crisis since the
Great Depression, financial institutions
face a challenging credit and
earnings cycle. Understandably, many
bank managers and boards of directors
are focusing efforts on areas of immediate
concern, such as liquidity and deteriorating
asset quality. However, evidence
suggests that more financial institutions
currently are taking on higher levels of
interest rate risk at a time when short-term
rates are near historic lows, which
could leave them significantly exposed to
changes in interest rates.

Interest rate risk (IRR)—the potential
for changes in interest rates to reduce a
bank’s earnings or economic value—is
inherent to banking. However, too much
IRR can leave bank capital and earnings
vulnerable, particularly for those financial
institutions in a weakened financial
condition. Interest rate fluctuations affect
earnings by changing net interest income
and other interest-sensitive income and
expense levels. Interest rate changes
affect capital by changing the net present
value of a bank’s future cash flows,
and the cash flows themselves, as rates
change.

Recent FDIC Call Report data suggest
financial institutions are becoming
increasingly liability sensitive and,
therefore, more exposed to increases in
interest rates. Factors contributing to
heightened IRR are earnings pressure to
offset losses and higher loan loss provisions;
elevated volumes of longer-term,
primarily mortgage, assets held in portfolio;
and heavy reliance on short-term and
wholesale funding sources that are generally
more rate sensitive and less stable than traditional deposits. Under these
circumstances, a significant increase in
interest rates could prove troublesome to
financial institutions not actively managing
their IRR exposure.

In light of the current environment,
it is critical that financial institutions
maintain a strong and effective IRR
management program that helps mitigate
exposure. This article describes the
current interest rate environment and
its relevance for the banking industry’s
IRR profile. The article then reviews IRR
measurement systems and cites best
practices for measuring, monitoring, and
controlling IRR.

Much of the discussion in this article
about the management of IRR exposures
is drawn from existing interagency
guidance,
the 1996 Policy Statement on
Interest Rate Risk (Policy Statement).1
The article does, however, provide additional
observations about best practices
for IRR management. The best practices
are noted from institutions with
strong IRR management frameworks
and are drawn from the authors’ experience,
as well as observations from FDIC
examinations.

The Current Rate Environment
and Bank Interest Rate Risk
Exposure

In the years before the current crisis,
interest rates steadily increased as
the Federal Reserve began to tighten
monetary policy, which was eased in
the wake of the 2001–2002 recession.
The onset of the financial crisis in 2007
prompted the Federal Reserve to take a
significantly more accommodative policy stance through a reduction in the federal
funds rate, among other initiatives.
Longer-term interest rates did not decline
commensurately, however, so that the
yield curve steepened considerably over
the last two years (see Chart 1).

Currently, short-term inflationary
expectations are subdued. However, it
is widely expected that, as the economy
recovers, short-term interest rates will
eventually return to more normal levels.
For example, one prominent survey of
economists forecasts 2010 to end under
a higher and flatter yield curve. The
forecast projects the federal funds rate
to increase gradually while longer-term
rates remain at or near current levels.2

A rising rate environment can reflect
stronger economic growth, good news
for an economy in recession. However,
rising short-term rates can compress
net interest margins (NIMs) as financial
institutions are forced to reprice funding;
some assets lose value as a result.
Thus, although bank earnings currently
are benefiting from a steep yield curve,
a change in monetary policy or investor sentiment could have a significant
adverse effect on financial institutions not
actively managing their IRR exposure.

In fact, recent financial reporting
suggests that financial institutions, particularly
small to midsize institutions, are
becoming more liability sensitive, which
elevates their exposure to rising rates. On
the liability side of the balance sheet, long-term
funds remain scarce due to investor
reluctance to lock into such low returns.
On the asset side, as a result of the continued
dislocation in the secondary and
commercial real estate markets, financial
institutions are holding longer-term assets,
primarily residential mortgage assets.

Maturities of Bank Assets
Are Lengthening

On the asset side of the balance sheet,
more financial institutions are holding
higher volumes of longer-term assets.3
For almost 20 percent of banks, longer-term
assets comprise more than half
of assets. This is up from 2006, when
longer-term assets made up the majority
of assets at only 11 percent of banks
(see Chart 2).

Chart 2: A Large Percentage of Banks Have Increased Exposure to Assets with
Extended Maturities

The current lengthening of asset
maturities is due in part to market
dynamics in the wake of the credit
crisis. Before the deterioration of the
mortgage markets, a large percentage of
small and midsize financial institutions
(those with under $10 billion in assets)
originated mortgages and sold them to
larger financial institutions, which then
pooled and securitized the loans. This
model, designed to transfer credit risk
from financial institutions to the capital
markets, resulted in large concentrations
of mortgage-related assets at the
largest institutions. The largest financial
institutions also originated mortgage
loans, often offering products with
which the community financial institutions could not compete. Instead, small
and midsize financial institutions found
a niche in commercial real estate lending,
specifically construction and development
(C&D) loans, which were kept
on their books. However, during the
past several quarters, small and midsize
financial institutions have increased
their exposure to long-term mortgage
loans and mortgage-related securities
and have reduced concentrations in
C&D loans. Although this process has
been critical to managing credit risk
within the industry, replacing C&D
loans, which tend to have a shorter duration
than mortgage assets, with assets
that have similar repricing characteristics
has been challenging (see Chart 3).

Chart 3: Institutions with Less than $10 Billion in Assets Are Shrinking C&D Portfolios,
but Are Increasing Holdings of Longer-Term Mortgages

The shift in the asset mix increases the
interest rate exposure of many institutions,
especially those with less than
$10 billion in total assets.4 Mortgage-related
assets present unique risks
because of borrowers’ ability to prepay
the mortgages before the contractual
term. Because prepayment rates slow
when rates rise, the duration of lower-coupon,
fixed-rate mortgages will extend,
and financial institutions will be locked
into these lower-yielding assets for longer
periods. Moreover, during the next few
years, mortgage exposures at small
and midsize financial institutions could
increase if federal programs aimed at
bolstering the housing market are wound
down (see Option Risk text box).5

Use of Less Stable Funding
Sources Remains High

Today, although bank funding sources
are more diverse, they continue to be
rate sensitive. During the past 15 years,
core deposit growth generally has remained flat.6 In response, financial
institutions have turned to other funding
sources such as noncore deposits and
wholesale funding products, which tend
to be driven by yield.7 If market conditions
change, noncore deposit customers
may rapidly transfer funds elsewhere,
and wholesale funds may reprice
quickly.8 The risk is particularly high for
those institutions with a high concentration
of longer-term assets, or about 40
percent of the industry (see Chart 4).

Chart 4: Noncore Funding Remains a Significant Funding Source for Institutions Where
Longer-Term Assets Are More than 40 Percent of Total Assets

Moreover, some less stable funding
sources are fundamentally more complex
than core deposits. For example, certain
wholesale funding agreements contain embedded options, such as call dates,
that would be exercised in a rising rate
environment. Embedded options are typically
beneficial to the provider of funds.
They can be disadvantageous, however,
to the recipient of funding who loses a
below market cost funding source (see
Option Risk text box).

Historically, the primary hedge against
IRR for most financial institutions was
a stable deposit base over which banks
had significant pricing power. Today,
however, competition for loans and
deposits has diluted pricing power as
commercial banks and thrifts compete
for customers with credit unions, insurance
companies, and other financial
firms. Moreover, advances in technology
and product delivery channels
have limited the relationship and direct
contact with many customers. As a
result, it is more challenging for institutions
to match funding terms with
assets or structure the balance sheet mix
to offset IRR mismatches effectively.
Additionally, banks could see their funding
costs rise to maintain and attract
deposits.

Another factor that could contribute to
higher funding costs in a rising interest
rate environment would be the marketplace
response to an unwinding of special
federal liquidity programs established
during the crisis. These government
support programs, directed at mitigating
the effects of considerable investor risk aversion, effectively reduced the interest
spreads financial institutions had to offer
to attract funding. As markets normalize,
and to the extent emergency federal
liquidity programs are phased out, interest
spreads offered by financial institutions
to attract funds could experience
upward pressure.

Option Risk

An option gives the holder the right, but
not the obligation, to buy, sell, or in some
manner alter the cash flow of an instrument
or financial contract. Option risk results
when a financial instrument’s cash flow
timing or amount can change as a result of
a decision taken by a counterparty, typically
in response to changes in interest rates.
This can negatively affect earnings or the
economic value of equity by reducing asset
yields, increasing funding costs, or reducing
the net present value of expected cash
flows.

Options may be distinct instruments, such
as exchange-traded and over-the-counter
contracts, or they may be embedded within
the contractual terms of an instrument.
Examples of instruments with embedded
options include callable or putable bonds
(such as callable U.S. Agency securities),
loans that give borrowers the right to prepay
balances without penalty (such as residential
mortgage loans), and deposit products
that give customers the right to withdraw
funds at any time without penalty (such as
Money Market Demand Accounts).

Typically, financial institutions are the
option sellers and the customers are the
option buyers, or option holders. Options,
both explicit and embedded, held by bank
customers are generally exercised to the
advantage of the holder, not the bank. If
not adequately managed, the asymmetrical
payoff characteristics of options can pose
risk to the option seller.

Options embedded in assets, liabilities,
and off-balance sheet derivatives can
create IRR. Embedded options can alter an instrument’s cash flow when interest rates
fluctuate, and can be in many instruments
and products, including the following:

Mortgage-backed securities

Callable bonds

Structured notes

Mortgage loans

Consumer loans

Derivatives

Non-maturity deposits

Federal Home Loan Bank borrowings

Trust preferred securities

On the asset side of the balance sheet,
prepayment options are the most prevalent
embedded option. Most residential
mortgage loans and many consumer loans
impose little or no prepayment penalty
on borrowers. Financial institutions also
may permit the prepayment of commercial
loans by not enforcing prepayment penalties.
Prepayment options create the risk
of contraction or extension of maturities.
When rates decline, borrowers will exercise
call options by prepaying loans, and a
bank’s asset maturities will shorten when
the institution would prefer them to extend.
Conversely, when rates rise, borrowers will
not prepay their loans, locking the bank into
a lower-yielding asset and making it difficult
for the bank to shorten asset maturities.
Contraction and extension risk also are
present in a similar fashion when financial
institutions invest in mortgage-backed securities
and other bonds with call options. A
bank that maintains a large portfolio of loans
and securities with embedded call options
heightens IRR due to a substantial increase
in the unpredictability of the cash flows.

Instruments with embedded call options
can demonstrate negative convexity.
Convexity describes the nonlinear element
of the price/yield relationship—in other
words, the imperfect correlation between
price and yield associated with fixed-income
instruments. The price of a bond with negative
convexity will increase more slowly than
the rate at which yields decline and will fall
faster than the rate at which yields rise. In
contrast, a bond with positive convexity will
rise in price faster than the rate at which
yields decline and will fall in price slower
than the rate at which yields rise. Option-free
instruments display positive convexity.

The liability side of the balance sheet
also contains embedded call options. Most
commonly, these embedded options take the
form of withdrawal rights in non-maturity
deposit (NMD) accounts. Customers have
the option to withdraw funds at any time.
These withdrawal option rights may be
exercised more frequently during periods of
volatile interest rates. For instance, when
interest rates rise, the market value of
the customer’s deposit generally declines
because changes in the rate paid on NMDs
lag increases in market rates. As a result,
the customer may initiate a withdrawal and
reduce a source of funding for the bank. Of
course, the bank can change the rate paid
on NMDs, which can be viewed as a type of
option as well. These liability-side options
can result in repricing risk if the deposits
are used to fund earning assets with different
repricing characteristics.

The confluence of these balance sheet
and economic trends has contributed to
an increased asset/liability mismatch
and set the stage for potential earnings
deterioration if interest rates rise.
Therefore,
it is critical that financial
institutions have and maintain on an
ongoing
basis an effective risk management
system.

Principles of Sound Interest
Rate Risk Management

To manage IRR exposure effectively,
financial institutions must have timely
and accurate information about the exposure
of their balance sheets to changes
in interest rates. The board of directors
should set the risk tolerances and set
policies that measure, monitor, and
control IRR exposures. Senior management
is charged with implementing the
approved guidelines, using appropriate
measurement systems, managing positions
to meet established risk limits, and
reporting IRR exposure. Management
also is charged with providing a system
of sound internal controls and appropriate
independent reviews to, among other
objectives, validate the robustness of
their forecasting models.9 The formality
and sophistication of an institution’s IRR
management should be commensurate
with its level of risk exposure and the
complexity of its holdings and activities.
Management should periodically assess
the institution’s business strategies and
new products or initiatives and the IRR
implications to ensure the risk management
process, including the measurement
model, remains appropriate.

Financial institutions with the most
robust interest rate risk measurement
systems quantify IRR by applying various
assumptions about future interest rates,
economic conditions, and customer
behavior to their current balance sheet
position.10 The intricacy of the measurement
system should vary depending
on the size, complexity, and business
model of the institution. Three types of
measurement tools generally provide the
foundation for IRR analysis: gap models,
economic valuation of equity (EVE)
models, and earnings simulation models.

Different levels of sophistication
characterize each model category, and
within categories complexity can vary.
A model’s sophistication usually depends
on the technical and mathematical
formulas underlying the measurement
system and the characteristics and types
of assumptions used. Models differ in
how they capture and reflect the four
fundamental types of IRR (see text box
on Types of Interest Rate Risk). The
following is an overview of gap, EVE, and
earnings simulation models:

Gap Analysis Models: Gap analysis
measures the difference between the
amount of interest-sensitive assets and
interest-sensitive liabilities that will
reprice (on a cumulative basis) during
a given time horizon. If a bank has a
negative gap, the amount of liabilities
repricing in a given period exceeds
the amount of assets repricing during
the same period, thus decreasing
net interest income in a rising rate
environment. The gap ratio can be
expressed as the percentage risk to
net interest income by multiplying the
gap ratio by the assumed rate change.
The result estimates the change to the
NIM. For example, a bank has a negative
15 percent one-year average gap.
If rates increase 2 percent, then the
NIM will decline 30 basis points (15
percent x .02). This estimate assumes
a static balance sheet and an immediate,
sustained interest rate shift.

Gap models are relatively simple
to prepare and understand. However,
they are limited, as they typically
cannot measure the effects of embedded
options, yield curve twists, and basis risk.11 Gap analysis can help
management visualize the time frames
in which repricing risk may occur, but
it should not be the primary analytical
tool for assessing IRR.

Types of Interest Rate Risk

There are four fundamental types of interest
rate risk:

Repricing risk results from timing differences
between coupon changes or cash flows
from assets, liabilities, and off-balance sheet
instruments. For example, long-term fixed-rate
securities funded by short-term deposits may
create repricing risk. If interest rates change,
then deposit funding costs will change more
quickly than the yield on the securities. Likewise,
the present value of the securities (i.e.,
their market price) will change more than the
value of the deposits, thereby affecting the
value of capital.

Basis risk results from weak correlation
between coupon-rate changes for assets,
liabilities, and off-balance sheet instruments.
For instance, LIBOR-based deposit rates may
change by 50 basis points, while prime-based
loan rates may change by only 25 basis points
during the same period. Basis risk originates
from the potential for market differences
when a position denominated in one currency
(USD) is used to offset an exposure marked to
another (Euro).

Yield curve risk results from changing rate
relationships between different maturities of
the same index. For example, a 30-year Treasury
bond’s yield may change by 200 basis
points, but a three-year Treasury note’s yield
may change by only 50 basis points during the
same period.

Option risk results when a financial instrument’s
cash flow timing or amount can
change as a result of a decision exercised by
a borrowing or lending counterparty, typically
in response to market interest rate changes.
This can adversely affect earnings by reducing
asset yields or increasing funding costs,
and it may reduce the net present value of
expected cash flows.

Economic Value of Equity Models:
EVE models reflect the net present
value of the institution’s assets, liabilities,
and off-balance sheet cash flows.
EVE models provide insights into a
bank’s longer-term IRR position. More
advanced versions of EVE models, if
administered correctly, can capture
all types of IRR. Financial institutions
should use EVE models capable of
capturing the level of risk and optionality
they have assumed.

EVE models range from simple
to sophisticated, depending on the
assumptions used to derive outputs,
and have advantages and shortcomings.
The most basic EVE models
use straightforward rate and cash
flow assumptions that are simple to
understand and easy to design. Basic
EVE models work well for noncomplex
financial institutions with simple
balance sheets. However, these simple
models often provide inaccurate valuations
of embedded options, possibly
understating risk, and should not be
used to assess more complex instruments.

Earnings Simulation Models: Earnings
simulation models measure the
effects interest rate changes will have
on interest income or net income.
Simulation models reflect a bank’s
income performance over time and
can, if properly calibrated, capture
the four types of IRR. Earnings
simulation models show the estimated
potential effects on earnings
and often are regarded by financial
institutions as having more utility
than other models. Many financial institutions
rely on earnings simulation
as the primary tool to measure,
manage, and control IRR exposure.
However, managers should be aware
that some optimistic assumptions
can be embedded in these models
that can affect their output. Managers
who review these models should
outline the rationale for determining
key assumptions and any changes to
assumptions and report to the Asset/Liability Management Committee
(ALCO), or similar management
committee.

Model outputs should proactively identify
risks that could deplete current capital
buffers or indicate the level of future
earnings at risk. Further, measurement
systems should enable management to
recognize risks stemming from new and
existing business strategies and have clear
and well-understood linkages between
changes in interest rates and resulting
changes in earnings and capital (see text
box on Interest Rate Risk Mitigation
Strategies).12 To properly measure IRR,
models should be calibrated to reflect
that not all assets will reprice simultaneously.
For example, variable-rate assets
with embedded caps or floors, where
the current interest rate is well beyond
the repricing limit, will behave more
like fixed-rate assets until interest rates
again approach the band where they
can adjust.

Scenario Analysis and Stress
Testing

IRR should be considered under a
range of potential scenarios, including
ones in which the balance sheet
is stressed or shocked significantly.
Stressed situations are those that reflect
significant movements in interest rates.
The output should reflect the subsequent
effect of such scenarios on earnings
(earnings simulation results) and the
underlying economic value of the bank’s
assets, liabilities, and off-balance sheet
items (EVE results).

The goal of stress testing is to identify
risk, not necessarily to estimate the most
likely interest rate scenario. The 1996
Interagency Policy Statement requires
that management consider “meaningful
stress situations” when modeling IRR,
providing for illustrative purposes a ±200
basis point rate change over a one-year
period. Many institutions have adopted
this scenario as the basis for stress testing.
However, in many cases, a ±200
basis point parallel shock will not be
sufficient for stress testing exposures. An
interest rate shock of at least ±300 basis
points would be more representative of a
severe movement in interest rates, given
the frequency and magnitude of observed historical interest rate movements. For
example, 30 percent of one-year periods
between 1955 and 2008 have experienced
changes in interest rates of more
than 200 basis points.13 Further, during
that extended period, rates changed by
more than 300 basis points almost 16
percent of the time, and more than 400
basis points about 9 percent of the time
(see Chart 5).

Chart 5: The Fed Funds Rate Has Spiked in Multiple Periods Over the Past 55 Years

Interest rate risk management is imperative
if exposure exceeds risk limits or capital
and earnings prove insufficient to withstand
adverse changes in interest rates. In such
cases an institution should reduce its interest
rate risk exposure, increase its capital,
or both. The primary tools for reducing
interest rate risk exposure are balance
sheet alteration and hedging.

Balance sheet alteration is the most
commonly used IRR management method.
Strategies include acquiring liabilities and
assets that have similar repricing, maturity,
and option characteristics. This strategy is
called cash flow matching, or matched funding.
Another strategy, duration matching,
attempts to align the duration of assets with
the duration of liabilities. Duration measures
the sensitivity of a financial instrument’s
value to changes in interest rates. Duration
depends on the timing and size of an instrument’s
cash flows, and, other things equal, is
higher for long-maturity instruments.

Hedging strategies often involve using
derivatives instruments. Examples of derivatives
are forward loan sales, swaps, futures,
forwards, cap options, floor options, collars,
and swaptions. The most common derivatives
used to hedge IRR are swaps and
forwards.14 These derivatives can reduce
an institution’s IRR if used correctly. For
example, a swap can effectively shorten
the duration of a commercial loan portfolio,
reducing an asset/liability mismatch.
Conversely, a bank could lengthen the
effective duration of its floating-rate wholesale
liabilities by entering into a swap
where a floating-rate stream of payments is
exchanged for a fixed-rate stream.

Hedging with interest rate derivatives can
be complex. If used incorrectly, derivatives
can compound risks rather than hedge
them, and institutions should not use derivatives
strategies without understanding
the risks and how cash flows will perform
under a variety of scenarios. Banks using
derivatives should incorporate the following
in a board-approved policy outlining the
bank’s hedging strategy:

Permissible strategies and types of
derivative contracts

Risk limits for hedging activity, such as
position limits (gross and net), maturity
parameters, and counterparty credit
guidelines, and procedures for monitoring
those limits

Names of individuals authorized to initiate
hedging transactions and establish limits
of authority

Description of how management will
hedge the asset or liability in question,
measure effectiveness and ensure
sufficient compliance with the technical
accounting guidance that governs
hedging activity, most notably Financial
Accounting Standards Board Statement
133 and its amendments

Banks that have not previously engaged
in derivatives-based hedging activities have
used outside consultants to assist in the
establishment of such a strategy. Institutions
that do this are reminded of the risks
of excessive reliance on third parties to
perform vital bank functions.15 The bank’s
board and management are accountable
for the results of any derivatives strategy,
regardless of whether the strategy is
recommended by a third party. The expectation
for fully understanding the risks of
the derivatives strategy is not diminished
by the use of a third party, and any bank
using derivatives hedging strategies should
adhere to sensible policy limits. Community
banks should use derivatives for risk mitigation
and not for speculative purposes, to
increase balance sheet exposures, or as
profit centers.

Examiners have observed that financial
institutions with the strongest IRR identification
and risk management programs have used interest rate shocks of ±400
basis points or more as a benchmark
and run multiple interest rate change
scenarios. Scenarios also should include
immediate interest rate changes, which
are necessary to capture all of the bank’s
option risk (such as call and prepayment
risks), which may be harder to
detect in scenarios that assume gradual
increases in rates. Additionally, scenarios
that consider non-parallel changes
in the slope of the yield curve and at
different points across the curve are
recommended.

The risk profile of an institution
will influence the types of stress testing
scenarios that will be necessary to
measure exposures adequately. As such,
smaller institutions and those with less
complex risk profiles may be able to run
fewer and less complicated scenarios.

Assumption Testing

Robust measurement of IRR requires
that management frequently assess the
reasonableness of a model’s underlying
assumptions. Although this may
seem basic, a best practice for strong
IRR management is ensuring that the
assumptions match the characteristics of
the bank’s profile. Management assumptions
should reflect the characteristics
of bank assets and liabilities and not
categorically rely on generic assumptions
provided by a vendor. In fact, reliance
on vendor-provided assumptions
that do not reflect the bank’s profile is
a common IRR management weakness
cited by FDIC examiners.

It is important that management use
model assumptions that adequately
reflect the risk profile of the institution’s
positions and products. Effective management
regularly reviews model assumptions
to ensure they are reasonable and
accurate. Assumptions should be well
documented. Backtesting, or comparing
model-predicted output to actual results,
is one way to check the reasonableness of
assumptions. Preferably, the backtesting period will be a period of stress or large
rate changes. If past estimates of IRR
exposure deviate significantly from actual
performance, different assumptions may
be appropriate. In such cases, management
should recalibrate its assumptions
to ensure the model remains effective.

A model may have many assumptions.
At a minimum, two basic assumptions
that should be included and continually
evaluated for reasonableness are asset
prepayments and non-maturity deposit
price sensitivity/decay rates. Customer
behaviors differ in various markets. As a
result, financial institutions with robust
IRR measurement systems perform both
historical and forward-looking analyses
to develop supportable assumptions
that are relevant to their market and
business plan.

Earnings simulations are dependent
on new business assumptions—mix,
maturity, and options. Assumptions
about product growth can mask IRR
exposure that exists in the balance sheet
and off-balance sheet positions. For
instance, a liability-sensitive bank may
show earnings increases during periods
of rising interest rates if favorable
new business product assumptions are
used in the model. Alternatively, earning
asset growth funded with wholesale
liabilities (leverage strategy) can earn
higher yields, despite adverse changes in
interest rates. Therefore, well-managed
institutions will run and report to their
ALCO or similar committee a static or
“no growth” scenario. To gain additional
insight, some financial institutions
choose to supplement the static model
with a dynamic model that assumes
growth in new business. However, such
dynamic models may be more relevant
for profit planning than for identifying
IRR risk. Additionally, other items should
be considered when setting assumptions
and running model scenarios, such as
yield curve shifts and twists, how asset
quality under changing rate scenarios
can influence assumptions, customer
behavior, and non-interest income fluctuations under changing rates (see
Assumptions text box).

Assumptions

Yield Curve Changes and Twists

Most financial institutions have a balance
sheet structure that benefits when the yield
curve is positive, normal, or upward sloping.
For the typical bank, a flattening yield curve or
a further inversion of the yield curve, if already
flat or inverted, likely poses the greatest risk to
future earnings. To capture this risk, financial
institutions should model for potential nonparallel
changes in the yield curve. Such a model
might consider a 400 basis point spontaneous
increase in short-term interest rates (for
example, three years and less) combined with
no change in longer-term interest rates (more
than three years). Financial institutions should
occasionally run supplemental models with
different pivot points to identify which point
best captures their risk.16

Asset Quality

Increases in market interest rates can
increase the rate of default on loans, adversely
affecting asset quality. Financial institutions
also should consider credit risk and pricing in
IRR models. For example, if a particular institution
has a large credit card portfolio, a wider
range of assumptions related to this exposure
would be expected in an earnings simulation
model. In such a case, management might
decide either to increase default assumptions
under a 400 basis point rate shock scenario
or not to reprice certain loan portfolios due to
credit risk constraints.

Customer Behavior

Appropriate assumptions about the interest
rate sensitivity of non-maturity deposits play a
key role in evaluating the IRR profile, even for
traditionally stable deposit relationships. As
previously discussed, financial institutions may
have less pricing power and thus less control
over balance sheet mix adjustments than they
enjoyed in the past.

Non-Interest Income

Many financial institutions also consider
the potential effects of interest rate movements
on non-interest income as an offset or
a “built-in” hedge to IRR. For example, a bank
with exposure to falling long-term rates may
see higher prepayments as mortgage borrowers
refinance, but at the same time experience
a significant jump in non-interest income from
increased mortgage refinancing. A bank likely
would include this offsetting IRR impact, if
substantial, in the monitoring report(s).

One method used to determine the
implications of model assumptions is
sensitivity testing. A sensitivity test alters
a key assumption to show how such a
change can affect model output. Effective
risk managers use sensitivity testing to
pinpoint the critical assumptions, which
offers them insights about how assumptions
influence measurement results. To
be meaningful, a sensitivity test must
alter the key assumptions significantly
enough to change model output. As a
best practice, assumption sensitivity testing
should be done at least annually and results should be presented to the ALCO
or a similar senior management committee,
and the board.

Internal Controls

An effective system of internal controls
should include enforcing official lines
of authority and appropriate segregation
of duties. The system of internal
controls should also include periodic
independent review and validation of
the measurement
system. Independent
review, which may be included in the
internal or external audit function,
should be performed on a regular basis
to ensure the integrity and accuracy of the IRR management process, including
board reporting. One of the most
common IRR management weaknesses
cited by FDIC examiners is the lack of an
adequate independent review.

Although the scope and formality of
the independent review and model
validation will depend on the size and
complexity of the institution, its activities,
and balance sheet composition,
even smaller financial institutions should
ensure that an independent party is
reviewing the IRR measurement and
reporting. Smaller institutions that do
not have internal audit functions or
lack the resources to outsource reviews
can meet the 1996 Policy Statement
guidelines by having a qualified staff
member—independent of the IRR
process—perform the reviews.

Internal control review should assess
data inputs and assumptions for accuracy,
completeness, and reasonableness.
As illustrated earlier, assumptions can
make or break the model output and are
critical to generating sound estimates of
IRR exposure.

In the absence of a third party, validation
testing may also be performed by
members of management who are independent
of the primary IRR management
function. Many institutions use backtesting
to help them validate risk measurement
calculations and model outputs.
In-depth validation of the mathematical
code and technical aspects of the model
is typically not performed at smaller,
noncomplex institutions, which often
rely on third-party vendors and software
packages to measure IRR. Instead, these
institutions should request third-party
review reports or audits of the service
provider’s model. Third-party vendors
typically provide such reports to clients
upon request as a matter of course. The FDIC considers it a best practice for institutions
to request and, if available, review
such reports on an annual basis.

Alternatively, the validation review
could include a review of the model by
a separate entity, or a run of a separate
model from that used at the institution.
The latter process can offer insight about
a model?s validity and is referred to as
“benchmarking.” The models and inputs
will not be identical but should be similar.
The results of the alternate (benchmark)
model are compared to the results
of the model used for IRR management
to identify any potential inconsistencies.
This process may be costly, but it is often
used by larger or more complex financial
institutions or those with significant IRR
exposure.

Financial institutions with large IRR
exposures or with concerns about
internal controls, model management,
or model efficacy may be required to
engage in a more formal external review.
This would likely involve one or both of
the methods described above.

Conclusion

Financial institutions should be vigilant
in their oversight and control of IRR
exposures. Given the current low interest
rate environment, it is important
that financial institutions plan for likely
increases in interest rates and take steps
to mitigate and control the associated
risks. Concentrations of longer-maturity
assets funded with shorter-maturity
liabilities can stress an institution’s earnings,
liquidity, and capital in a rising
rate environment. Financial institutions
should be prepared to manage the risk of
declining yield spreads between longer-term
investments, loans, and other assets
and shorter-term deposits and other liabilities. If capital and earnings provide
insufficient protection against adverse
changes in interest rates, a bank should
take steps to reduce its IRR exposure,
increase capital, or both.

3 Longer-term assets are defined here as those maturing or repricing in three or more years.

4 The decline of adjustable-rate mortgage originations and the process of large financial institutions bringing off-balance sheet (for example, structured investment
vehicle) assets on balance sheet also are factors driving the increase in longer-term assets.

5 To free up liquidity among mortgage originators, the Federal Reserve established the Mortgage-Backed Securities (MBS) Purchase Program beginning January
5, 2009 and set a goal of buying up to $1.25 trillion of agency MBS, which also helped lower mortgage rates. The New York Fed has purchased more than $790
billion of agency MBS since the program began, which represents nearly half of all domestic mortgage originations in 2009. As the federal programs are scaled
back, MBS prices and yields will normalize, and MBS bank holdings are anticipated to continue to increase.

6 In the wake of the financial crisis and implementation of higher insurance limits and programs such as the
Temporary Liquidity Guarantee Program, which guaranteed non-interest bearing transaction deposits, a significant
amount of deposits came into the banking system. Going forward, it is anticipated that some portion of
deposits will leave the banking system as customers search for higher yields.

7 Generally, the relative stability of funding is difficult to determine with precision from Call Report data, and
“noncore” funding cited here is only a rough estimate. The stability of each bank’s funding mix should be
assessed on a case-by-case basis using all available data on product characteristics, including management
deposit stability studies.

8 Many financial institutions offer certificates of deposit through listing services and deposit accounts through
Internet channels. These deposits, if less than $100,000, will not fall within the technical definition of “brokered”
or “noncore,” and are not identified as volatile funding sources in regulatory reports. Nevertheless, these deposits
exhibit many of the same rate sensitive and volatility characteristics as brokered deposits. Therefore, Chart 4
likely understates the actual increase in dependency on volatile funding sources. These points re-emphasize the
importance of a closer evaluation of deposit stability characteristics.

10 The assumptions used to derive output are key components of a bank’s measurement system. Numerous
assumptions can be included in IRR measurement systems, including the projected level of interest rates,
non-maturity deposit price sensitivity/decay rates, prepayment speeds, and customer behavior.

11 Some variations of gap, known as “dynamic gap” models, do attempt to capture some of these risks.

12 Financial institutions should use caution when combining budgeting and IRR modeling methodologies. Financial
planning and budgeting models often contain loan growth and funding assumptions that, when incorporated
into
interest rate measurement models, can mask underlying risk exposures. Management should run a “no growth”
scenario to ensure the current position is measured. Since budgeting and risk management have different objectives,
they should be evaluated differently.

14 Several exchange-traded hedging options are available to community banks that in certain circumstances
could help reduce a bank’s exposure to IRR. For example, the Chicago Mercantile Exchange and affiliated
Chicago Board of Trade offer swaps, options, and futures based on LIBOR and U.S. Treasury notes, as well
as other interest rates. Over-the-counter (OTC) or bilateral agreements are another option, often available to
community banks through correspondent banks and sometimes Federal Home Loan Banks. Although they are
currently more widely used and often are simpler for banks to manage, OTC derivatives can present larger
counterparty
risk (the risk that the party holding the other side of a transaction will not be able to make good on
its commitment) than those traded on an exchange.

16 The three-year pivot point example is an observed practice at certain institutions running effective non-parallel
yield curve twists. If a bank has more pronounced balance sheet exposure a different durations, then the use of
a different pivot point could be justified.